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Methods for analysis of the cancer microenvironment and their potential for disease prediction, monitoring and personalized treatments
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
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2012 (English)In: The EPMA journal, ISSN 1878-5085, Vol. 3, no 7Article, review/survey (Refereed) Published
Abstract [en]

A tumor does not consist of a homogenous population of cancer cells. Therefore, to understand cancer, the tumor microenvironment and the interplay between the different cell types present in the tumor has to be taken into account, and how this regulates the growth and survival of the cancer cells. To achieve a full picture of this complex interplay, analysis of tumor tissue should ideally be performed with cellular resolution, providing activity status of individual cells in this heterogeneous population of different cell-types. In addition, in situ analysis provides information on the architecture of the tissue wherein the cancer cells thrive, providing information of the identity of neighboring cells that can be used to understand cell-cell communication. Herein we describe how padlock probes and in situ PLA can be used for visualization of nucleic acids and protein activity, respectively, directly in tissue sections, and their potential future role in personalized medicine.

Place, publisher, year, edition, pages
2012. Vol. 3, no 7
Keyword [en]
Picea, Qinghai Tibetan Plateau, effective population size, divergence time, introgression, speciation
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-176989DOI: 10.1007/s13167-012-0140-3PubMedID: 22738217OAI: oai:DiVA.org:uu-176989DiVA: diva2:538473
Available from: 2012-06-29 Created: 2012-06-29 Last updated: 2013-03-08Bibliographically approved

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Clausson, Carl-MagnusNilsson, MatsSöderberg, Ola

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Molecular toolsScience for Life Laboratory, SciLifeLabDepartment of Immunology, Genetics and Pathology
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